| 来源类型 | Discussion paper
|
| 规范类型 | 论文
|
| 来源ID | DP13114
|
| DP13114 Enforcing Regulation under Illicit Adaptation |
| [unavailable]
|
| 发表日期 | 2018-08-13
|
| 出版年 | 2018
|
| 语种 | 英语
|
| 摘要 | Attempts to curb illegal activity by enforcing regulations gets complicated when agents react to the new regulatory regime in unanticipated ways to circumvent enforcement. We present a research strategy that uncovers such reactions, and permits program evaluation net of such adaptive behaviors. Our interventions were designed to reduce over-fishing of the critically endangered Pacific hake by either (a) monitoring and penalizing vendors that sell illegal fish or (b) discouraging consumers from purchasing using an information campaign. Vendors attempt to circumvent the ban through hidden sales and other means, which we track using mystery shoppers. Instituting random monitoring visits are much more effective in reducing true hake availability by limiting such cheating, compared to visits that occur on a predictable schedule. Monitoring at higher frequency (designed to limit temporal displacement of illegal sales) backfires, because targeted agents learn faster, and cheat more effectively. Sophisticated policy design is therefore crucial for determining the sustained, longer-term effects of enforcement. Data collected from fishermen, vendors, and consumers allow us to document the upstream, downstream, spillover, and equilibrium effects of enforcement on the entire supply chain. The consumer information campaign generates two-thirds of the gains compared to random monitoring, but is simpler for the government to implement and almost as cost-effective. |
| 主题 | Development Economics
; Public Economics
|
| 关键词 | Enforcement
Regulation
Law and economics
Over-fishing
|
| URL | https://cepr.org/publications/dp13114
|
| 来源智库 | Centre for Economic Policy Research (United Kingdom)
|
| 资源类型 | 智库出版物
|
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/541917
|
推荐引用方式
GB/T 7714 |
[unavailable]. DP13114 Enforcing Regulation under Illicit Adaptation. 2018.
|
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
